Robust Monitoring of Time Series with Application to Fraud Detection

Unsupervised Fraud Detection in Time Series data

Fraud detection is of great importance to financial institutions. This paper is concerned with the problem of finding outliers in time series financial data using Peer Group Analysis (PGA), which is an unsupervised technique for fraud detection. The objective of PGA is to characterize the expected pattern of behavior around the target sequence in terms of the behavior of similar objects, and th...

Application of Fuzzy Logic to Fraud Detection

for management override of controls. Auditors are discouraged from placing too much reliance on client representation and are required to maintain a skeptical attitude throughout the audit. The standard encourages auditors to engage in frequent discussion among engagement personnel regarding the risk of material misstatement due to fraud. SAS 99 also requires auditors to inquire of management a...

Using Application-Aware Flow Monitoring for SIP Fraud Detection

Credit Card Fraud Detection using Time Series Analysis

Credit card usage has been increased tremendously because of the popularity of E-commerce. As the usage of credit card grows the occurrence of fraudulent transactions also increases, thus comes the stipulation of fraud detection. Detection of fraudulent transaction using credit card plays a vital role in financial institutions. In the proposed work, fraud detection is done with data mining appr...

Discovering Local Subgroups, with an Application to Fraud Detection

In Subgroup Discovery, one is interested in finding subgroups that behave differently from the ‘average’ behavior of the entire population. In many cases, such an approach works well because the general population is rather homogeneous, and the subgroup encompasses clear outliers. In more complex situations however, the investigated population is a mixture of various subpopulations, and reporti...